Nombre de documents archivés : 3.
    Madaeni, Fatemehalsadat
  
(2023).
Deep Learning Models and Their Interpretability for Ice-Jam Prediction in the Province of Quebec
	Thèse.
Québec, Université du Québec, Institut national de la recherche scientifique, Doctorat en sciences de l'eau, 160 p.
  
    Madaeni, Fatemehalsadat; Chokmani, Karem  ORCID: https://orcid.org/0000-0003-0018-0761; Lhissou, Rachid; Homayouni, Saeid
ORCID: https://orcid.org/0000-0003-0018-0761; Lhissou, Rachid; Homayouni, Saeid  ORCID: https://orcid.org/0000-0002-0214-5356; Gauthier, Yves et Tolszczuk-Leclerc, Simon
  
(2022).
Convolutional neural network and long short-term memory models for ice-jam predictions.
    The Cryosphere
	  , vol. 16
	  , nº 4.
	
     pp. 1447-1468.
     DOI: 10.5194/tc-16-1447-2022.
ORCID: https://orcid.org/0000-0002-0214-5356; Gauthier, Yves et Tolszczuk-Leclerc, Simon
  
(2022).
Convolutional neural network and long short-term memory models for ice-jam predictions.
    The Cryosphere
	  , vol. 16
	  , nº 4.
	
     pp. 1447-1468.
     DOI: 10.5194/tc-16-1447-2022. 
  
  
    Madaeni, Fatemehalsadat; Lhissou, Rachid; Chokmani, Karem  ORCID: https://orcid.org/0000-0003-0018-0761; Raymond, Sébastien et Gauthier, Yves
  
(2020).
Ice jam formation, breakup and prediction methods based on hydroclimatic data using artificial intelligence: A review.
    Cold Regions Science and Technology
	  , vol. 174
	  .
	
     p. 103032.
     DOI: 10.1016/j.coldregions.2020.103032.
ORCID: https://orcid.org/0000-0003-0018-0761; Raymond, Sébastien et Gauthier, Yves
  
(2020).
Ice jam formation, breakup and prediction methods based on hydroclimatic data using artificial intelligence: A review.
    Cold Regions Science and Technology
	  , vol. 174
	  .
	
     p. 103032.
     DOI: 10.1016/j.coldregions.2020.103032. 
  
  
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